4 Visually and Interactively Exploring Our Data

Now that we have set admin to be the loaded administrative area data and roads to be the loaded roads data, we can use sf to plot their geometry on a map:

plot(st_geometry(admin), axes = TRUE)

Here we chose to show the axis, giving a general idea of what coordinates each state/UT is located at. We also show the polygonal boundaries to give us an idea of how large each state/UT is.

plot(st_geometry(roads), axes = TRUE)

Since road data is generally polylines, and we are using all road without considering their classification, we can simply plot just the lines. This gives us an idea of which areas in India have more roads (are more road dense) than that of others (mostly south and eastern India due to the darker areas).

In addition to the static mapping we just did, we can also use mapview to interactively explore our data. It’s pretty cool - try it out!:

mapview(admin, viewer.suppress = F)

mapview(roads, viewer.suppress = F)

Next, we will use sf, lwgeom, and mapview to extract road lengths and vertices, and to geoaggregate them into our states/UTs.